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Surveillance Nation

Webcams, tracking devices, and interlinked databases are leading to the elimination of unmonitored public space. Are we prepared for the consequences of the intelligence-gathering network we’re unintentionally building?

Route 9 is an old two-lane highway that cuts across Massachusetts from Boston in the east to Pittsfield in the west. Near the small city of Northampton,the highway crosses the wide Connecticut River.The Calvin Coolidge Memorial Bridge, named after the president who once served as Northampton’s mayor, is a major regional traffic link.When the state began a long-delayed and still-ongoing reconstruction of the bridge in the summer of 2001, traffic jams stretched for kilometers into the bucolic New England countryside.

In a project aimed at alleviating
drivers’ frustration, the University of
Massachusetts Transportation Center,
located in nearby Amherst, installed eight
shoe-size digital surveillance cameras
along the roads leading to the bridge.
Six are mounted on utility poles and the
roofs of local businesses. Made by Axis
Communications in Sweden, they are
connected to dial-up modems and transmit images of the roadway before them to
a Web page, which commuters can check
for congestion before tackling the road.
According to Dan Dulaski, the system’s
technical manager, running the entire
webcam system—power, phone, and
Internet fees—costs just $600 a month.
The other two cameras in the
Coolidge Bridge project are a little less
routine. Built by Computer Recognition
Systems in Wokingham, England, with
high-quality lenses and fast shutter speeds
(1/10,000 second), they are designed to photograph every car and truck that
passes by. Located eight kilometers apart,
at the ends of the zone of maximum traffic congestion, the two cameras send
vehicle images to attached computers,
which use special character-recognition
software to decipher vehicle license plates.
The license data go to a server at the
company’s U.S. office in Cambridge, MA, about 130 kilometers away. As each
license plate passes the second camera,the
server ascertains the time difference
between the two readings. The average of
the travel durations of all successfully
matched vehicles defines the likely travel
time for crossing the bridge at any given
moment, and that information is posted
on the traffic watch Web page

To local residents, the traffic data are
helpful, even vital: police use the information to plan emergency routes. But as
the computers calculate traffic flow, they
are also making a record of all cars that
cross the bridge—when they do so, their
average speed, and (depending on lighting and weather conditions) how many
people are in each car.

Trying to avoid provoking privacy
fears, Keith Fallon, a Computer Recognition Systems project engineer, says,
“we’re not saving any of the information we capture. Everything is deleted
immediately.” But the company could
change its mind and start saving the
data at any time. No one on the road
would know

The Coolidge Bridge is just one of
thousands of locations around the planet
where citizens are crossing—willingly,
more often than not—into a world of
networked, highly computerized surveillance.According to a January report by J.P.
Freeman, a security market-research firm
in Newtown, CT, 26 million surveillance
cameras have already been installed worldwide, and more than 11 million of them
are in the United States. In heavily moni-
tored London, England, Hull University
criminologist Clive Norris has estimated,
the average person is filmed by more than
300 cameras each day.

The $150 million-a-year remote
digital-surveillance-camera market will
grow, according to Freeman, at an
annual clip of 40 to 50 percent for the
next 10 years. But astonishingly, other,
non-video forms of monitoring will
increase even faster. In a process that
mirrors the unplanned growth of the
Internet itself, thousands of personal,
commercial, medical, police, and government databases and monitoring sys-
tems will intersect and entwine.
Ultimately, surveillance will become so
ubiquitous, networked, and searchable
that unmonitored public space will effectively cease to exist.

It’s not all about Big Brother or Big
Business, either. Widespread electronic
scrutiny is usually denounced as a creation of political tyranny or corporate
greed. But the rise of omnipresent surveillance will be driven as much by ordinary citizens’ understandable—even
laudatory—desires for security, control,
and comfort as by the imperatives of business and government. “Nanny cams,”
global-positioning locators, police and
home security networks, traffic jam monitors,medical-device radio-frequency tags,
small-business webcams: the list of monitoring devices employed by and for average Americans is already long, and it will
only become longer. Extensive surveillance, in short, is coming into being
because people like and want it.

“Almost all of the pieces for a surveillance society are already here,” says
Gene Spafford, director of Purdue University’s Center for Education and
Research in Information Assurance and
Security.”It’s just a matter of assembling
them.” Unfortunately, he says, ubiquitous surveillance faces intractable social
and technological problems that could
well reduce its usefulness or even make it
dangerous.As a result, each type of monitoring may be beneficial in itself, at least
for the people who put it in place, but the
collective result could be calamitous.

To begin with, surveillance data from
multiple sources are being combined into
large databases. For example, businesses
track employees’ car, computer, and telephone use to evaluate their job performance; similarly, the U.S. Defense
Department’s experimental Total Information Awareness project has announced
plans to sift through information about
millions of people to find data that identify criminals and terrorists.

But many of these merged pools of
data are less reliable than small-scale,
localized monitoring efforts; big databases
are harder to comb for bad entries, and
their conclusions are far more difficult to
verify. In addition, the inescapable nature
of surveillance can itself create alarm,
even among its beneficiaries. “Your little
camera network may seem like a good
idea to you,” Spafford says. “Living with
everyone else’s could be a nightmare.”

THE SURVEILLANCE AD-HOCRACY

Last October deadly snipers terrorized
Washington, DC, and the surrounding
suburbs, killing 10 people. For three
long weeks, law enforcement agents
seemed helpless to stop the murderers,
who struck at random and then vanished
into the area’s snarl of highways. Ultimately, two alleged killers were arrested,
but only because their taunting messages
to the authorities had inadvertently provided clues to their identification.

In the not-too-distant future, according to advocates of policing technologies, such unstoppable rampages may
become next to impossible, at least in
populous areas. By combining police
cameras with private camera networks
like that on Route 9, video coverage will
become so complete that any snipers
who waged an attack—and all the people
near the crime scene—would be trackable
from camera to camera until they could
be stopped and interrogated.

Examples are legion. By 2006, for
instance, law will require that every U.S.
cell phone be designed to report its precise location during a 911 call; wireless
carriers plan to use the same technology
to offer 24-hour location-based services,
including tracking of people and vehicles.
To prevent children from wittingly or
unwittingly calling up porn sites, the
Seattle company N2H2 provides Web
filtering and monitoring services for
2,500 schools serving 16 million students. More than a third of all large corporations electronically review the
computer files used by their employees,
according to a recent American Management Association survey. Seven of
the 10 biggest supermarket chains use
discount cards to monitor customers’
shopping habits: tailoring product offerings to customers’ wishes is key to survival in that brutally competitive
business. And as part of a new, federally
mandated tracking system, the three
major U.S. automobile manufacturers plan to put special radio transponders
known as radio frequency identification
tags in every tire sold in the nation. Far
exceeding congressional requirements,
according to a leader of the Automotive
Industry Action Group, an industry think
tank, the tags can be read on vehicles
going as fast as 160 kilometers per hour
from a distance of 4.5 meters.

Many if not most of today’s surveillance networks were set up by government and big business, but in years to
come individuals and small organizations
will set the pace of growth.Future sales of
Net-enabled surveillance cameras, in the
view of Fredrik Nilsson, Axis Communications’ director of business development,
will be driven by organizations that buy
more than eight but fewer than 30 cameras—condo associations,church groups,
convenience store owners, parent-teacher
associations, and anyone else who might
like to check what is happening in one
place while he is sitting in another. A
dozen companies already help working
parents monitor their children’s nannies
and day-care centers from the office; scores
more let them watch backyards, school
buses, playgrounds, and their own living
rooms.Two new startups—Wherify Wire-
less in Redwood Shores, CA, and Peace of
Mind at Light Speed in Westport,CT—are
introducing bracelets and other portable
devices that continuously beam locating
signals to satellites so that worried moms
and dads can always find their children.

As thousands of ordinary people buy
monitoring devices and services, the
unplanned result will be an immense,
overlapping grid of surveillance systems,
created unintentionally by the same ad-
hocracy that caused the Internet to
explode. Meanwhile, the computer net-
works on which monitoring data are
stored and manipulated continue to grow
faster, cheaper, smarter, and able to store
information in greater volume for longer
times. Ubiquitous digital surveillance
will marry widespread computational
power—with startling results.

The factors driving the growth of
computing potential are well known.
Moore’s law—which roughly equates to
the doubling of processor speed every 18
months—seems likely to continue its
famous march. Hard drive capacity is rising even faster. It has doubled every year
for more than a decade, and this should go
on “as far as the eye can see,”according to Robert M.Wise, director of product maketing for the desktop product group at
Maxtor, a hard drive manufacturer. Similarly, according to a 2001 study by a pair
of AT&T Labs researchers,network trans-
mission capacity has more than doubled
annually for the last dozen years, a tendency that should continue for at least
another decade and will keep those powerful processors and hard drives well fed
with fresh data.

Today a company or agency with a
$10 million hardware budget can buy
processing power equivalent to 2,000
workstations, two petabytes of hard drive
space (two million gigabytes, or 50,000
standard 40-gigabyte hard drives like
those found on today’s PCs), and a two-
gigabit Internet connection (more than
2,000 times the capacity of a typical home
broadband connection). If current trends
continue, simple arithmetic predicts that
in 20 years the same purchasing power
will buy the processing capability of 10
million of today’s workstations, 200
exabytes (200 million gigabytes) of storage capacity, and 200 exabits (200 million
megabits) of bandwidth. Another way
of saying this is that by 2023 large organizations will be able to devote the
equivalent of a contemporary PC to monitoring every single one of the 330
million people who will then be living in
the United States.

One of the first applications for this
combination of surveillance and compu-
tational power,says Raghu Ramakrishnan,
a database researcher at the University of
Wisconsin-Madison, will be continuous
intensive monitoring of buildings,offices,
and stores: the spaces where middle-class
people spend most of their lives. Surveillance in the workplace is common now: in
2001, according to the American Management Association survey, 77.7 percent
of major U.S. corporations electronically
monitored their employees, and that
statistic had more than doubled since
1997. But
much more is on the way. Companies
like Johnson Controls and Siemens,
Ramakrishnan says, are already “doing
simplistic kinds of ‘asset tracking,’as they
call it.” They use radio frequency identification tags to monitor the locations of
people as well as inventory. In January,
Gillette began attaching such tags to 500
million of its Mach 3 Turbo razors. Special “smart shelves” at Wal-Mart stores
will record the removal of razors by shop-
pers, thereby alerting stock clerks whenever shelves need to be refilled—and effectively transforming Gillette customers
into walking radio beacons. In the future,
such tags will be used by hospitals to
ensure that patients and staff maintain
quarantines,by law offices to keep visitors
from straying into rooms containing
clients’ confidential papers,and in kindergartens to track toddlers.

By employing multiple, overlapping
types of monitoring, Ramakrishnan says,
managers will be able to “keep track of
people, objects, and environmental levels
throughout a whole complex.” Initially,
these networks will be installed for “such
mundane things as trying to figure out
when to replace the carpets or which
areas of lawn get the most traffic so you
need to spread some grass seed preven-
tively.”But as computers and monitoring
equipment become cheaper and more
powerful, managers will use surveillance
data to construct complex, multidimensional records of how spaces are used. The
models will be analyzed to improve efficiency and security—and they will be
sold to other businesses or governments.
Over time, the thousands of individual
monitoring schemes inevitably will merge
together and feed their data into large
commercial and state-owned networks.
When surveillance databases can describe
or depict what every individual is doing
at a particular time, Ramakrishnan says,
they will be providing humankind with
the digital equivalent of an ancient dream:
being “present, in effect, almost anywhere
and anytime.”

GARBAGE IN, GRAGBEA OTU

In 1974 Francis Ford Coppola wrote
and directed The Conversation, which
starred Gene Hackman as Harry Caul,
a socially maladroit surveillance expert. In
this remarkably prescient movie, a mysterious organization hires Caul to record
a quiet discussion that will take place in
the middle of a crowd in San Francisco’s
Union Square. Caul deploys three microphones: one in a bag carried by a confederate and two directional mikes
installed on buildings overlooking the
area. Afterward Caul discovers that each
of the three recordings is plagued by
background noise and distortions, but
by combining the different sources, he is
able to piece together the conversation.
Or, rather, he thinks he has pieced it
together. Later, to his horror, Caul learns that he misinterpreted a crucial line, a discovery that leads directly to the movie’s
chilling denouement.

The Conversation illustrates a central dilemma for tomorrow’s surveillance
society. Although much of the explosive
growth in monitoring is being driven by
consumer demand, that growth has not
yet been accompanied by solutions to
the classic difficulties computer systems
have integrating disparate sources of
information and arriving at valid conclusions. Data quality problems that cause
little inconvenience on a local scale—
when Wal-Mart’s smart shelves misread a
razor’s radio frequency identification
tag—have much larger consequences
when organizations assemble big databases from many sources and attempt to
draw conclusions about, say, someone’s
capacity for criminal action. Such problems, in the long run, will play a large role
in determining both the technical and
social impact of surveillance.

The experimental and controversial
Total Information Awareness program of
the Defense Advanced Research Projects
Agency exemplifies these issues. By merging records from corporate,medical,retail,
educational, travel, telephone, and even
veterinary sources, as well as such “biometric”data as fingerprints,iris and retina
scans, DNA tests, and facial-characteristic
measurements,the program is intended to
create an unprecedented repository of
information about both U.S. citizens and
foreigners with U.S. contacts. Program
director John M. Poindexter has explained that analysts will use custom data-mining
techniques to sift through the mass of
information, attempting to “detect, classify, and identify foreign terrorists” in
order to “preempt and defeat terrorist
acts”—a virtual Eye of Sauron, in critics’
view, constructed from telephone bills
and shopping preference cards.

In February Congress required the
Pentagon to obtain its specific approval
before implementing Total Information
Awareness in the United States (though
certain actions are allowed on foreign
soil). But President George W. Bush had
already announced that he was creating
an apparently similar effort, the Terrorist
Threat Integration Center, to be led by the
Central Intelligence Agency. Regardless of
the fate of these two programs, other
equally sweeping attempts to pool monitoring data are proceeding apace.Among
these initiatives is Regulatory DataCorp,
a for-profit consortium of 19 top financial institutions worldwide. The consortium, which was formed last July,
combines members’ customer data in an
effort to combat “money laundering,
fraud, terrorist financing, organized
crime, and corruption.” By constantly
poring through more than 20,000 sources
of public information about potential
wrongdoings—from newspaper articles
and Interpol warrants to disciplinary
actions by the U.S. Securities and
Exchange Commission—the consortium’s Global Regulatory Information
Database will, according to its owner,
help clients “know their customers.”

Equally important in the long run
are the databases that will be created by
the nearly spontaneous aggregation of
scores or hundreds of smaller databases.
“What seem to be small-scale, discrete
systems end up being combined into large
databases,” says Marc Rotenberg, executive
director of the Electronic Privacy Information Center,a nonprofit research organization in Washington, DC. He points to
the recent, voluntary efforts of merchants
in Washington’s affluent Georgetown district. They are integrating their in-store
closed-circuit television networks and making the combined results available to
city police. In Rotenberg’s view, the collection and consolidation of individual
surveillance networks into big government and industry programs “is a strange
mix of public and private, and it’s not
something that the legal system has
encountered much before.”

Managing the sheer size of these
aggregate surveillance databases, surprisingly, will not pose insurmountable
technical difficulties. Most personal data
are either very compact or easily com-
pressible. Financial, medical, and shopping records can be represented as strings
of text that are easily stored and transmitted; as a general rule, the records do
not grow substantially over time.

Even biometric records are no strain
on computing systems.To identify people,
genetic-testing firms typically need
stretches of DNA that can be represented
in just one kilobyte—the size of a short e-
mail message. Fingerprints, iris scans,
and other types of biometric data consume little more. Other forms of data
can be preprocessed in much the way
that the cameras on Route 9 transform
multi-megabyte images of cars into short
strings of text with license plate numbers
and times. (For investigators, having a
video of suspects driving down a road
usually is not as important as simply
knowing that they were there at a given
time.) To create a digital dossier for every
individual in the United States—as pro-
grams like Total Information Awareness would require—only “a couple terabytes
of well-defined information” would be
needed, says Jeffrey Ullman, a former
Stanford University database researcher.
“I don’t think that’s really stressing the
capacity of [even today’s] databases.”

Instead, argues Rajeev Motwani,
another member of Stanford’s database
group, the real challenge for large surveillance databases will be the seemingly
simple task of gathering valid data. Computer scientists use the term GIGO—
garbage in, garbage out—to describe
situations in which erroneous input cre-ates erroneous output.Whether people are
building bombs or buying bagels, governments and corporations try to predict their behavior by integrating data
from sources as disparate as electronic
toll-collection sensors, library records,
restaurant credit-card receipts, and grocery store customer cards—to say nothing
of the Internet, surely the world’s largest
repository of personal information.
Unfortunately, all these sources are full of
errors, as are financial and medical
records. Names are misspelled and digits
transposed; address and e-mail records
become outdated when people move and
switch Internet service providers; and
formatting differences among databases
cause information loss and distortion
when they are merged. “It is routine to
find in large customer databases defective
records—records with at least one major
error or omission—at rates of at least 20
to 35 percent,”says Larry English of Information Impact, a database consulting
company in Brentwood, TN.

Unfortunately, says Motwani, “data
cleaning is a major open problem in the
research community. We are still struggling to get a formal technical definition
of the problem.” Even when the original
data are correct, he argues, merging them
can introduce errors where none had
existed before.Worse, none of these worries about the garbage going into the system even begin to address the still larger problems with the garbage going out.

THE DISSOLUTION OF PRIVACY

Almost every computer-science student takes a course in algorithms.
Algorithms are sets of specified,
repeatable rules or procedures for accomplishing tasks such as sorting numbers;
they are, so to speak, the engines that
make programs run. Unfortunately, innovations in algorithms are not subject to
Moore’s law, and progress in the field is
notoriously sporadic.”There are certain
areas in algorithms we basically can’t do
better and others where creative work
will have to be done,” Ullman says. Sifting
through large surveillance databases for
information, he says, will essentially be “a
problem in research in algorithms. We
need to exploit some of the stuff that’s
been done in the data-mining community
recently and do it much, much better.”
Working with databases requires
users to have two mental models. One is a model of the data. Teasing out answers
to questions from the popular search
engine Google, for example, is easier if
users grasp the varieties and types of
data on the Internet—Web pages with
words and pictures, whole documents in
a multiplicity of formats, downloadable
software and media files—and how they
are stored. In exactly the same way,
extracting information from surveillance
databases will depend on a user’s knowledge of the system. “It’s a chess game,”
Ullman says.”An unusually smart analyst
will get things that a not-so-smart one
will not.”

Second, and more important according to Spafford, effective use of big surveillance databases will depend on having
a model of what one is looking for. This
factor is especially crucial, he says, when
trying to predict the future, a goal of
many commercial and government projects. For this reason, what might be called
reactive searches that scan recorded data
for specific patterns are generally much
more likely to obtain useful answers than
proactive searches that seek to get ahead
of things. If, for instance, police in the
Washington sniper investigation had been able to tap into a pervasive network of
surveillance cameras, they could have
tracked people seen near the crime scenes
until they could be stopped and questioned: a reactive process.But it is unlikely
that police would have been helped by
proactively asking surveillance databases
for the names of people in the Washington area with the requisite characteristics
(family difficulties, perhaps, or military
training and a recent penchant for drinking) to become snipers.

In many cases, invalid answers are
harmless. If Victoria’s Secret mistakenly
mails 1 percent of its spring catalogs to
people with no interest in lingerie, the
price paid by all parties is small. But if a
national terrorist-tracking system has
the same 1 percent error rate, it will produce millions of false alarms, wasting
huge amounts of investigators’ time and,
worse, labeling many innocent U.S. citi-
zens as suspects.”A 99 percent hit rate is
great for advertising,”Spafford says,”but
terrible for spotting terrorism.”

Because no system can have a success rate of 100 percent, analysts can try to
decrease the likelihood that surveillance
databases will identify blameless people as
possible terrorists. By making the criteria
for flagging suspects more stringent, officials can raise the bar, and fewer ordinary
citizens will be wrongly fingered.
Inevitably, however, that will mean also
that the “borderline” terrorists—those
who don’t match all the search criteria
but still have lethal intentions—might be
overlooked as well. For both types of error,
the potential consequences are alarming.

Yet none of these concerns will stop
the growth of surveillance, says Ben
Shneiderman, a computer scientist at the
University of Maryland.Its potential benefits are simply too large. An example is
what Shneiderman, in his recent book
Leonardo’s Laptop: Human Needs and the
New Computing Technologies, calls the
World Wide Med: a global, unified database that makes every patient’s complete
medical history instantly available to doctors through the Internet,replacing today’s scattered sheaves of paper records.”The idea,”he
says, “is that if you’re brought to an ER
anywhere in the world, your medical
records pop up in 30 seconds.” Similar
programs are already coming into existence. Backed by the Centers for Disease
Control and Prevention, a team based at
Harvard Medical School is planning to
monitor the records of 20 million walk-in
hospital patients throughout the United
States for clusters of symptoms associated with bioterror agents.Given the huge
number of lost or confused medical
records, the benefits of such plans are
clear. But because doctors would be continually adding information to medical
histories,the system would be monitoring
patients’ most intimate personal data.The
network, therefore, threatens to violate
patient confidentiality on a global scale.

In Shneiderman’s view, such trade-offs are inherent to surveillance. The
collective by-product of thousands of
unexceptionable,even praiseworthy efforts
to gather data could be something nobody
wants: the demise of privacy.”These networks are growing much faster than
people realize,” he says.”We need to pay
attention to what we’re doing right now.”

In The Conversation, surveillance
expert Harry Caul is forced to confront the
trade-offs of his profession directly. The
conversation in Union Square provides
information that he uses to try to stop a
murder. Unfortunately, his faulty interpretation of its meaning prevents him
from averting tragedy. Worse still, we see
in scene after scene that even the expert
snoop is unable to avoid being monitored and recorded.At the movie’s intense,
almost wordless climax, Caul rips his
home apart in a futile effort to find the
electronic bugs that are hounding him.

The Conversation foreshadowed a view
now taken by many experts: surveillance
cannot be stopped.There is no possibility
of “opting out.” The question instead is
how to use technology, policy, and shared
societal values to guide the spread of surveillance—by the government, by corporations, and perhaps most of all by our
own unwitting and enthusiastic participation—while limiting its downside.

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